The long range goal of this project is to quantitatively characterize the epithelium of human urinary bladder from scanned digitized images of stained sections using digital computers and to develop a data-directed taxonomy for the range of tissues from normal to invasive carcinoma. Tissue sections were prepared on microscopic slides at St. Vincent Hospital, Worcester, Mass. and stained with hematoxylin. They were scanned at the Jet Propulsion Laboratory, Pasadena, Calif. so that the resulting images were at 630X, sampled at half micron intervals and rendered in 256 linear gray levels. The material was routine clinical preparations of variable and sometimes mediocre quality. The absorption peak for the tissue sections was determined to be at 570NM and all scans were made at both this wave length and in white light. In one experiment with tissue sections stained with gallocyanin chromalum, the response in the entire visible range was assessed. The PEEP-DECIDE-GRAPH system was used to analyze the digitized images. (In fact, the project was the impetus for implementing that system, which is discussed in a separate project report.) All of the object extraction methods were applied to digitized images of tissue sections. They met with varying degrees of success and depending on the quality of the tissue sections one or another method may be necessary. Two morphologically distinct tissue sections were chosen for in-depth study. Both yielded to thresholding for obtaining nuclear images. The entire armamentarium of PEEP features was extracted on approximately 20 nuclei from each tissue. Linear and quadratic discriminant analysis were used to learn each tissue section as a category. Specimens from each tissue were then classified with the following result of demonstrated internal consistency: nuclei in one tissue type were overwhelmingly more like each other than like cell nuclei from other tissue types. The data directed classification of tissue sections might well be an improvement over current subjective and often dubious decisions. The difficulty of the undertaking should not be underemphasized. Classification using algorithms may lead to greater objectivity, public verifiability, and greater consistency. There is always the opportunity for discovering new significant differences in optical properties between papillomas and papillary carcinomas using the digital (Text Truncated - Exceeds Capacity)